Using uniform distribution definition from Wikipedia ("all intervals of the same length on the distribution's support are equally probable") we get P(X \in [0,1)) = P(X \in [1, 2)) = P(X \in [2, 3)) = ...

By countable additivity P(\Omega) = P(X \in [0, \infty)) = P(X \in [0, 1)) + P(\X \in [1, 2)) + ... = P(X \in [0, 1)) + P(X \in [0, 1)) + ...

And this evaluates to 0 if P(X \in [0, 1)) = 0 and to \infty if P(\X \in [0, 1)) > 0.